Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath
Open accessAbstract
Two of the biggest challenges in medicine today are the need to detect diseases in a noninvasive manner and to differentiate between patients using a single diagnostic tool. The current study targets these two challenges by developing a molecularly modified silicon nanowire field effect transistor (SiNW FET) and showing its use in the detection and classification of many disease breathprints (lung cancer, gastric cancer, asthma, and chronic obstructive pulmonary disease). The fabricated SiNW FETs are characterized and optimized based on a training set that correlate their sensitivity and selectivity toward volatile organic compounds (VOCs) linked with the various disease breathprints. The best sensors obtained in the training set are then examined under real-world clinical conditions, using breath samples from 374 subjects. Analysis of the clinical samples show that the optimized SiNW FETs can detect and discriminate between almost all binary comparisons of the diseases under examination with >80% accuracy. Overall, this approach has the potential to support detection of many diseases in a direct harmless way, which can reassure patients and prevent numerous unpleasant investigations.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ANN model-assisted Si-nanowire FETs detected volatile organic compounds in breath prints from lung cancer, gastric cancer, and asthma and chronic obstructive pulmonary disease patients, and early diagnostic stages of cancer.
“Another example of using wearable AI-based biosensors is the detection of volatile organic compounds (VOCs) using ANN model-assisted Si-nanowire FETs in breath prints from lung cancer, gastric cancer, and asthma and chronic obstructive pulmonary disease patients, and early diagnostic stages of cancer [214,215].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [215]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Siegel, R. L., Miller, K. D., & Jemal, A. (2015) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21254 · Cited by 11,854 · see citing works
A survey on feature selection methods
Chandrashekar, G., & Sahin, F. (2014) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.11.024 · Cited by 5,189 · see citing works
Artificial neural networks: fundamentals, computing, design, and application
Basheer, I. A., & Hajmeer, M. N. (2000) · Journal of Microbiological Methods · doi:10.1016/s0167-7012(00)00201-3 · Cited by 3,234 · see citing works
Introduction to Multivariate Analysis
Lee, J. C., Chatfield, C., & Collins, A. J. (1983) · Technometrics · doi:10.2307/1267862 · Cited by 1,787 · see citing works
Results of Initial Low-Dose Computed Tomographic Screening for Lung Cancer
The National Lung Screening Trial Research Team (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1209120 · Cited by 1,083 · see citing works
Volatile Organic Compounds of Lung Cancer and Possible Biochemical Pathways
Hakim, M., Broza, Y. Y., Barash, O., Peled, N., Phillips, M., Amann, A., & Haick, H. (2012) · Chemical Reviews · doi:10.1021/cr300174a · Cited by 953 · see citing works
Self-citationAssessment, origin, and implementation of breath volatile cancer markers
Haick, H., Broza, Y. Y., Mochalski, P., Ruzsányi, V., & Amann, A. (2013) · Chemical Society Reviews · doi:10.1039/c3cs60329f · Cited by 644 · see citing works
Self-citationThe overlap syndrome of asthma and COPD: what are its features and how important is it?
Gibson, P. G., & Simpson, J. L. (2009) · Thorax · doi:10.1136/thx.2008.108027 · Cited by 607 · see citing works
Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath
Machado, R. F., Laskowski, D. M., Deffenderfer, O., Burch, T., Zheng, S., Mazzone, P. J., Mekhail, T. M., Jennings, C. A., Stoller, J. K., Pyle, J., et al. (2005) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200409-1184oc · Cited by 600 · see citing works
Noninvasive detection of lung cancer by analysis of exhaled breath
Bajtarevic, A., Ager, C., Pienz, M., et al. (2009) · BMC Cancer · doi:10.1186/1471-2407-9-348 · Cited by 598 · see citing works
Wang, C., & Sahay, P. (2009) · Sensors · doi:10.3390/s91008230 · Cited by 597 · see citing works
Detection of Lung Cancer With Volatile Markers in the Breatha
Phillips, M., Cataneo, R. N., Cummin, A. R. C., Gagliardi, A. J., Gleeson, K., Greenberg, J. H., Maxfield, R. A., & Rom, W. N. (2003) · CHEST Journal · doi:10.1378/chest.123.6.2115 · Cited by 567 · see citing works
Sensors for Breath Testing: From Nanomaterials to Comprehensive Disease Detection
Konvalina, G., & Haick, H. (2014) · Accounts of Chemical Research · doi:10.1021/ar400070m · Cited by 561 · see citing works
Self-citationGastric cancer: Prevention, screening and early diagnosis
Пасечников, В. Д. (2014) · World Journal of Gastroenterology · doi:10.3748/wjg.v20.i38.13842 · Cited by 435 · see citing works
Current status of clinical breath analysis
Risby, T. H., & Solga, S. F. (2006) · Applied Physics B · doi:10.1007/s00340-006-2280-4 · Cited by 363 · see citing works
Nanomaterial-Based Sensors for Detection of Disease by Volatile Organic Compounds
Broza, Y. Y., & Haick, H. (2013) · Nanomedicine · doi:10.2217/nnm.13.64 · Cited by 356 · see citing works
Self-citationHybrid Volatolomics and Disease Detection
Broza, Y. Y., Mochalski, P., Ruzsányi, V., Amann, A., & Haick, H. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201500153 · Cited by 291 · see citing works
Self-citationA nanomaterial-based breath test for distinguishing gastric cancer from benign gastric conditions
Xu, Z.-Q., Broza, Y. Y., Ionsecu, R., Tisch, U., Ding, L., Liu, H., Song, Q., Pan, Y.-Y., Xiong, F.-X., Gu, K.-S., et al. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.44 · Cited by 270 · see citing works
Self-citationBiochemical Profile of Uremic Breath
Simenhoff, M. L., Burke, J. F., Saukkonen, J. J., Ordinario, A. T., Doty, R. L., & Dunn, S. (1977) · New England Journal of Medicine · doi:10.1056/nejm197707212970303 · Cited by 247 · see citing works
Artificial sensing intelligence with silicon nanowires for ultraselective detection in the gas phase
Wang, B., Cancilla, J. C., Torrecilla, J. S., & Haick, H. (2014) · Nano Letters · doi:10.1021/nl404335p · Cited by 236 · see citing works
Self-citationFilter-Free Image Sensor Pixels Comprising Silicon Nanowires with Selective Color Absorption
Park, H.-S., Dan, Y., Seo, K., et al. (2014) · Nano Letters · doi:10.1021/nl404379w · Cited by 233 · see citing works
Tisch, U., Schlesinger, I., Ionescu, R., Nassar, M., Axelrod, N., Robertman, D., Tessler, Y., Azar, F., Marmur, A., Aharon‐Peretz, J., et al. (2012) · Nanomedicine · doi:10.2217/nnm.12.105 · Cited by 223 · see citing works
Self-citationDiagnosis of head-and-neck cancer from exhaled breath
Hakim, M., Billan, S., Tisch, U., et al. (2011) · British Journal of Cancer · doi:10.1038/bjc.2011.128 · Cited by 217 · see citing works
Detection of precancerous gastric lesions and gastric cancer through exhaled breath
Amal, H., Leja, M., Funka, K., Škapars, R., Sīviņš, A., Ancāns, G., Liepniece‐Karele, I., Ķikuste, I., Lašina, I., & Haick, H. (2015) · Gut · doi:10.1136/gutjnl-2014-308536 · Cited by 214 · see citing works
Self-citationNanoscale Sensor Technologies for Disease Detection via Volatolomics
Vishinkin, R., & Haick, H. (2015) · Small · doi:10.1002/smll.201501904 · Cited by 198 · see citing works
Self-citationNon-invasive Breath Analysis of Pulmonary Nodules
Peled, N., Hakim, M., Bunn, P. A., Miller, Y. E., Kennedy, T. C., Mattei, J., Mitchell, J. D., Hirsch, F. R., & Haick, H. (2012) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e3182637d5f · Cited by 194 · see citing works
Self-citationBreath testing as potential colorectal cancer screening tool
Amal, H., Leja, M., Funka, K., Lašina, I., Škapars, R., Sīviņš, A., Ancāns, G., Ķikuste, I., Vanags, A., Tolmanis, I., et al. (2015) · International Journal of Cancer · doi:10.1002/ijc.29701 · Cited by 188 · see citing works
Self-citationFleischer, M., Simon, E., Rumpel, E., et al. (2002) · Sensors and Actuators B Chemical · doi:10.1016/s0925-4005(01)01056-5 · Cited by 171 · see citing works
Konvalina, G., & Haick, H. (2011) · ACS Applied Materials & Interfaces · doi:10.1021/am2013695 · Cited by 150 · see citing works
Self-citationEnhanced Sensing of Nonpolar Volatile Organic Compounds by Silicon Nanowire Field Effect Transistors
Paska, Y., Stelzner, T., Christiansen, S. H., & Haick, H. (2011) · ACS Nano · doi:10.1021/nn201184c · Cited by 149 · see citing works
Self-citationWang, B., Huynh, T., Wu, W., et al. (2016) · Advanced Materials · doi:10.1002/adma.201505641 · Cited by 148 · see citing works
Assessment of ovarian cancer conditions from exhaled breath
Amal, H., Shi, D., Ionescu, R., et al. (2014) · International Journal of Cancer · doi:10.1002/ijc.29166 · Cited by 143 · see citing works
Ionescu, R., Broza, Y. Y., Shaltieli, H., Sadeh, D., Zilberman, Y., Feng, X., Glass‐Marmor, L., Lejbkowicz, I., Müllen, K., Miller, A., et al. (2011) · ACS Chemical Neuroscience · doi:10.1021/cn2000603 · Cited by 135 · see citing works
Self-citationMiekisch, W., & Schubert, J. K. (2006) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2006.05.006 · Cited by 133 · see citing works
Interactive Effect of Hysteresis and Surface Chemistry on Gated Silicon Nanowire Gas Sensors
Paska, Y., & Haick, H. (2012) · ACS Applied Materials & Interfaces · doi:10.1021/am300288z · Cited by 118 · see citing works
Self-citationAmann, A., Mochalski, P., Ruzsányi, V., Broza, Y. Y., & Haick, H. (2014) · Journal of Breath Research · doi:10.1088/1752-7155/8/1/016003 · Cited by 108 · see citing works
Self-citationMolecular Gating of Silicon Nanowire Field-Effect Transistors with Nonpolar Analytes
Paska, Y., Stelzner, T., Assad, O. N., Tisch, U., Christiansen, S. H., & Haick, H. (2011) · ACS Nano · doi:10.1021/nn203653h · Cited by 105 · see citing works
Self-citationDetecting active pulmonary tuberculosis with a breath test using nanomaterial-based sensors
Nakhleh, M. K., Jeries, R., Gharra, A., Binder, A. B., Broza, Y. Y., Mellissa, P., Dheda, K. U. J., & Haick, H. (2014) · European Respiratory Journal · doi:10.1183/09031936.00019114 · Cited by 104 · see citing works
Self-citationMonolayer-Capped Gold Nanoparticles for Disease Detection From Breath
Nakhleh, M. K., Broza, Y. Y., & Haick, H. (2014) · Nanomedicine · doi:10.2217/nnm.14.121 · Cited by 103 · see citing works
Self-citationNickel hydroxide modified silicon nanowires electrode for hydrogen peroxide sensor applications
Yan, Q., Wang, Z., Zhang, J., et al. (2011) · Electrochimica Acta · doi:10.1016/j.electacta.2011.11.098 · Cited by 95 · see citing works
Innovative Food Processing Technologies: Advances in Multiphysics Simulation
(2011) · Wiley eBooks · doi:10.1002/9780470959435 · Cited by 93 · see citing works
pH-Control System Based on Artificial Neural Networks
Palancar, M. C., Aragón, J. M., & Torrecilla, J. S. (1998) · Industrial & Engineering Chemistry Research · doi:10.1021/ie970718w · Cited by 89 · see citing works
Self-citationAssessment of Ovarian Cancer Conditions From Exhaled Breath
Amal, H., Shi, D.-Y., Ionescu, R., et al. (2015) · Obstetrical & Gynecological Survey · doi:10.1097/ogx.0000000000000154 · Cited by 80 · see citing works
Human breath analysis: methods for sample collection and reduction of localized background effects
Martin, A. N., Farquar, G. R., Jones, A. D., & Frank, M. A. (2009) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-009-3217-7 · Cited by 79 · see citing works
Lou, L., Zhang, S., Park, W., et al. (2012) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/22/5/055012 · Cited by 78 · see citing works
Effect of Functional Groups on the Sensing Properties of Silicon Nanowires toward Volatile Compounds
Wang, B., & Haick, H. (2013) · ACS Applied Materials & Interfaces · doi:10.1021/am4004649 · Cited by 78 · see citing works
Self-citationSilicon nanowires based resistors as gas sensors
Demami, F., Ni, L., Rogel, R., et al. (2011) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2011.04.083 · Cited by 75 · see citing works
Chemical Passivation of Silicon Nanowires with C1−C6 Alkyl Chains through Covalent Si−C Bonds
Bashouti, M. Y., Stelzner, T., Berger, A., Christiansen, S. H., & Haick, H. (2008) · The Journal of Physical Chemistry C · doi:10.1021/jp8077437 · Cited by 71 · see citing works
Self-citationBashouti, M. Y., Stelzner, T., Christiansen, S. H., & Haick, H. (2009) · The Journal of Physical Chemistry C · doi:10.1021/jp905394w · Cited by 64 · see citing works
Self-citationSpray-Coating Route for Highly Aligned and Large-Scale Arrays of Nanowires
Assad, O. N., Leshansky, A. M., Wang, B., Stelzner, T., Christiansen, S. H., & Haick, H. (2012) · ACS Nano · doi:10.1021/nn204513y · Cited by 59 · see citing works
Self-citationEffect of Chain Length on the Sensing of Volatile Organic Compounds by means of Silicon Nanowires
Wang, B., & Haick, H. (2013) · ACS Applied Materials & Interfaces · doi:10.1021/am401265z · Cited by 58 · see citing works
Self-citationDiscontinuous Molecular Films Can Control Metal/Semiconductor Junctions
Haick, H., Ambrico, M., Ligonzo, T., et al. (2004) · Advanced Materials · doi:10.1002/adma.200400923 · Cited by 57 · see citing works
Self-citationGeographical variation in the exhaled volatile organic compounds
Amal, H., Leja, M., Broza, Y. Y., Tisch, U., Funka, K., Liepniece‐Karele, I., Škapars, R., Xu, Z.-Q., Liu, H., & Haick, H. (2013) · Journal of Breath Research · doi:10.1088/1752-7155/7/4/047102 · Cited by 55 · see citing works
Self-citationVishinkin, R., Assad, O. N., Zigelboim, K., Wang, B., & Haick, H. (2013) · ACS Applied Materials & Interfaces · doi:10.1021/am403421g · Cited by 49 · see citing works
Self-citationA comparative evaluation of filter-based feature selection methods for hyper-spectral band selection
Wu, B., Chen, C., Kechadi, T., et al. (2013) · International Journal of Remote Sensing · doi:10.1080/01431161.2013.827815 · Cited by 48 · see citing works
Phillips, M. (1992) · International Archives of Occupational and Environmental Health · doi:10.1007/bf00381479 · Cited by 46 · see citing works
Torrecilla, J. S., Tortuero, C., Cancilla, J. C., et al. (2013) · Talanta · doi:10.1016/j.talanta.2013.03.060 · Cited by 45 · see citing works
Self-citationSensor arrays based on nanoparticles for early detection of kidney injury by breath samples
Nakhleh, M. K., Amal, H., Awad, H., et al. (2014) · Nanomedicine Nanotechnology Biology and Medicine · doi:10.1016/j.nano.2014.06.007 · Cited by 40 · see citing works
H2 sensing properties of modified silicon nanowires
Ahmed, L. B., Naama, S., Keffous, A., et al. (2015) · Progress in Natural Science Materials International · doi:10.1016/j.pnsc.2015.03.003 · Cited by 30 · see citing works
Halpern, J. M., Wang, B., & Haick, H. (2015) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.5b01721 · Cited by 25 · see citing works
Self-citationPaska, Y., & Haick, H. (2009) · Applied Physics Letters · doi:10.1063/1.3266858 · Cited by 22 · see citing works
Self-citationCancilla, J. C., Díaz‐Rodríguez, P., Matute, G., et al. (2015) · Physical Chemistry Chemical Physics · doi:10.1039/c4cp04679j · Cited by 15 · see citing works
Self-citationWang, H., Fan, P., Tong, B., et al. (2015) · Advanced Functional Materials · doi:10.1002/adfm.201401632 · Cited by 14 · see citing works
Rapid Low‐Temperature 3D Integration of Silicon Nanowires on Flexible Substrates
Kim, Y., Kim, H., Kim, J. H., et al. (2015) · Small · doi:10.1002/smll.201500378 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The emergence of AI-based wearable sensors for digital health technology: a review
Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535 · see citing works
Advanced Materials for Health Monitoring with Skin‐Based Wearable Devices
Jin, H., Abu‐Raya, Y. S., & Haick, H. (2017) · Advanced Healthcare Materials · doi:10.1002/adhm.201700024 · Cited by 317 · see citing works
Self-citationArtificial Intelligence in Medical Sensors for Clinical Decisions
Haick, H., & Tang, N. (2021) · ACS Nano · doi:10.1021/acsnano.1c00085 · Cited by 231 · see citing works
Self-citationPeng, B., Zhao, F., Ping, J., & Ying, Y. (2020) · Small · doi:10.1002/smll.202002681 · Cited by 224 · see citing works
Flexible Plasmonic Biosensors for Healthcare Monitoring: Progress and Prospects
Song, L., Chen, J., Xu, B. B., & Huang, Y. (2021) · ACS Nano · doi:10.1021/acsnano.1c07176 · Cited by 186 · see citing works
Biomedical Implants with Charge‐Transfer Monitoring and Regulating Abilities
Wang, D., Tan, J., Zhu, H., Mei, Y., & Liu, X. (2021) · Advanced Science · doi:10.1002/advs.202004393 · Cited by 49 · see citing works
- Authors
- Shehada, N., Cancilla, J. C., Torrecilla, J. S., Pariente, E. S., Brönstrup, G., Christiansen, S., Johnson, D. W., Leja, M., Davies, M. P. A., Liran, O., Peled, N., & Haick, H.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- Universidad Complutense de Madrid (ES)
- Department of Chemical Engineering, Complutense University of Madrid, Madrid 28040, Spain
- Max Planck Institute for the Science of Light (DE)
- Helmholtz-Zentrum Berlin für Materialien und Energie (DE)
- Baptist Cancer Center (US)
- Faculty of Medicine, University of Latvia, 19 Raiņa boulv., LV1586 Riga, Latvia
- University of Liverpool (GB)
- Tel Aviv University (IL)
- Corresponding author
- Haick, Hossam
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-07-14
- Volume
- 10
- Issue
- 7
- Pages
- 7047-7057
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2461893227
- Cited by
- 227
- References
- 64
- Citations by year
- 2026: 9 · 2025: 19 · 2024: 17 · 2023: 15 · 2022: 27 · 2021: 35 · 2020: 30 · 2019: 17 · 2018: 30 · 2017: 23 · 2016: 4
- FWCI
- 11.89
- Type
- journal article
- Language
- en
- Open access
- Licence
- other-oa
- Locations
- ACS Nano (publishedVersion)
- PubMed (publishedVersion)
- HZB Repository (Helmholtz-Zentrum Berlin für Materialien und Energie GmbH (HZB)) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- European Commission (644031)
- Seventh Framework Programme (258868)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Chemical Sensor Technologies
- Physical Sciences › Engineering › Biomedical Engineering › Nanowire Synthesis and Applications
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Gas Sensing Nanomaterials and Sensors
- Keywords
- silicon nanowire transistors, breath analysis, breath biomarkers, volatile organic compounds, lung cancer, gastric cancer, asthma, chronic obstructive pulmonary disease, disease classification, non-invasive diagnosis
- MeSH terms
- Asthma, Breath Tests, Humans, Lung Diseases, Silicon, Nanowires, Volatile Organic Compounds
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
